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The task consists of programming a Python implementation of a solver for the Decanting Task.
Assume you have 3 vessels, vessel 1 capable of holding 5 litres of milk, vessel 2 capable of holding 3 litres and vessel 3 capable of holding 8 litres. The starting state is the first vessel is filled to the limit (i.e. 5 litres), vessel 2 is also filled to the limit (3 litres), and vessel 3 is empty:
One can now pour the contents of one vessel into another one, without spilling, and stopping when the target vessel is filled. The task is the following: by pouring back and forth, how can one split the total of 8 litres of milk into two equal portions of 4 litres each? How can one pour the contents of the vessels from one to another such that at the end of the pouring process, one vessel should contain 4 litres and another one also 4 litres. The following considerations apply: it is not allowed to estimate quantities by eye. In pouring the contents from one vessel to another, one stops either when the pouring vessel is empty, or when the target vessel is full. One can not do a partial decanting.
The Task
Based on the search algorithms covered in the lecture, write a Python program that starts from some starting state, (f
1
,f
2
,f
3
) and moves according to the rules until it reaches a given goal
state for the decanting task.
2 Task: Bayesian Update A Whale Watching Scenario
2.1 Description
The task consists of writing a Python program which simulates a ship trying to reach a whale in a 10 × 10 grid world. More precisely, the ship moves through the grid world and measures (e.g. by sonar) a distance to the whale. From it, it deduces where the whale could be (using a Bayesian model), moves, measures again, etc. until it knows where the whale
The Task
The task of this assignment is to fill in the missing parts of the program, indicated by three dots
in the Python program
whale_fillin.py
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